Ensemble evaluation of potential distribution of Procambarus clarkii using multiple species distribution models.

Procambarus clarkii is a notorious invasive species that has led to ecological concerns owing to its high viability and rapid reproduction. South Korea, a country exposed to a high risk of introduction of invasive species due to active international trade, has suffered from recent massive invasions by invasive species, necessitating the evaluation of potential areas requiring intensive monitoring. In this study, we developed two different types of species distribution models, CLIMEX and random forest, for P. clarkii using occurrence records from the United States. The potential distribution in the United States was predicted along coastal lines and inland regions located below 40°N latitude The model was then applied to evaluate the potential distribution in South Korea, and an ensemble map was constructed to identify the most vulnerable domestic regions. According to both models, the domestic potential distribution was highest in most areas located at low altitudes. In the ensemble model, most of the low-altitude western regions, the eastern coast, and some southern inland regions were predicted to be suitable for the distribution of P. clarkii, and a similar distribution pattern was predicted when the model was projected into the future climate. Through this study, it is possible to secure basic data that can be used for the early monitoring of the introduction and subsequent distribution of P. clarkii.

Assessing potential European areas of Pierce's disease mediated by insect vectors by using spatial ensemble model.

Pierce's disease (PD) is a serious threat to grape production in Europe. This disease is caused by Xylella fastidiosa and is mediated by insect vectors, suggesting its high potential for spread and necessity for early monitoring. In this study, hence, potential distribution of Pierce's disease varied with climate change and was spatially evaluated in Europe using ensemble species distribution modeling. Two models of X. fastidiosa and three major insect vectors (Philaenus spumarius, Neophilaenus campestris, and Cicadella viridis) were developed using CLIMEX and MaxEnt. The consensus areas of the disease and insect vectors, along with host distribution, were evaluated using ensemble mapping to identify high-risk areas for the disease. Our predictions showed that the Mediterranean region would be the most vulnerable to Pierce's disease, and the high-risk area would increase three-fold due to climate change under the influence of N. campestris distribution. This study demonstrated a methodology for species distribution modeling specific to diseases and vectors while providing results that could be used for monitoring Pierce's disease by simultaneously considering the disease agent, vectors, and host distribution.

Spatial analysis of the occurrence of the western conifer seed bug Leptoglossus occidentalis (Heteroptera: Coreidae) in Europe based on multiple environmental variables.

The western conifer seed bug (WCSB) Leptoglossus occidentalis (Heidemann) (Heteroptera: Coreidae) is a pest insect that causes significant losses of coniferous trees worldwide. In this study, we sought to project the potential distribution of the WCSB based on dual CLIMEX modeling and random forest (RF) analysis to obtain basic data for WCSB monitoring strategies. The CLIMEX model, a semimechanistic niche model that responds to climate-based environmental parameters, is a species distribution model that focuses on regional climatic suitability. Given that this model can be used to select areas that are likely to reflect the climatically favorable spread of species, which we initially used CLIMEX to evaluate the potential distribution of the WCSB. The RF algorithm was used to predict the potential occurrence of WCSB and to evaluate the relative importance of environmental variables for WCSB occurrence. Using the RF model, land cover was found to be the most important variable for classifying the presence/pseudo-absence of the WCSB, with an accuracy of 77.1%. Climatic suitability for the WCSB was predicted to be 2.4-fold higher in Southern Europe than in Western Europe, and the WCSB was predicted to occur primarily near coniferous forests. Given that CLIMEX and RF analyses yielded different prediction results, using the findings of both models may compensate for the shortcomings of these models when used independently. Consequently, to ensure greater prediction reliability, we believe that it would be beneficial to base predictions on the combined potential distribution data obtained using both modeling approaches.

Spatial ensemble modeling for predicting the potential distribution of Lymantria dispar asiatica (Lepidoptera: Erebidae: Lymantriinae) in South Korea.

The spongy moth, Lymantria dispar, is a pest that damages various tree species throughout North America and Eurasia, has recently emerged in South Korea, threatening local forests and landscapes. The establishment of effective countermeasures against this species' outbreak requires predicting its potential distribution with climate change. In this study, we used species distribution models (CLIMEX and MaxEnt) to predict the potential distribution of the spongy moth and identify areas at risk of exposure to a sustained occurrence of the pest by constructing an ensemble map that simultaneously projected the outcomes of the two models. The results showed that the spongy moth could be distributed over the entire country under the current climate, but the number of suitable areas would decrease under a climate change scenario. This study is expected to provide basic data that can predict areas requiring intensive control and monitoring in advance with methodologically improved modeling technique.

Evaluation of Spatial Distribution of Three Major Leptocorisa (Hemiptera: Alydidae) Pests Using MaxEnt Model.

We targeted three major Leptocorisa species (L. chinensis, L. acuta, and L. oratoria) and evaluated their potential distributions using MaxEnt. The results showed that most Asian countries and northern Australia would be suitable for at least one of these pest species, and climate change will expand their habitat northward. All of the developed models were evaluated to be excellent with AUC, TSS, and OR10%. Most of the recorded regions of the Leptocorisa species are consistent with the result of potential distributions predicted in this study. The results confirmed that the minimum temperature of the coldest month mainly influences the three Leptocorisa species distributions. The potential distributions of the three species cover major rice cultivation areas regardless of climate change, suggesting that it would be necessary to establish a sustainable control strategy for the pests.

Sweep Sampling Comparison of Terrestrial Insect Communities Associated with Herbaceous Stratum in the Riparian Zone of the Miho River, Korea.

To investigate insect and plant community relationships in riparian zones, terrestrial insect communities were compared in plant communities in the riparian zone of the Miho River, Korea. The sweep netting method was used to sample insects in 50 m transects in three herbaceous plant communities. In 2020, each plant community-Chenopodium album, Beckmannia syzigachne, and Artemisia indica-was swept 100 times (50 sweeps × 2). In 2021, two communities had an additional 100 sweeps collected using 10 subsamples of 10 sweeps (excluding C. album communities). The surveyed dominant species or subdominant species of the insect community in each site preyed on the dominant plant species at the site. The Bray-Curtis similarity was significantly higher than the Sørensen similarity when comparing datasets across different years for the same plant species community. The predicted optimum sampling size to obtain approximately 80% of the total species estimated to be at each survey site, for effective quantitative collection of terrestrial insect herbivores in each plant community, was examined. Fifty sweeps were required for the A. indica community and 100 sweeps were required for the B. syzigachne community. The results of this study provide important data for riparian biodiversity conservation and future pest monitoring.

Evaluation of the suitability of potato cultivation areas in South Korea based on climate and soil conditions.

BACKGROUND: Changes in dietary patterns have led to a decrease in rice consumption, raising demands for the cultivation of alternative crops that meet the current requirements. Potatoes are highly productive and can be stored for a relatively long period, thereby ensuring adequate income for farmers; however, optimal cultivation is necessary to maximize yield. OBJECTIVE: This study proposes optimal cultivation regions for potato considering climate and soil conditions. MATERIALS AND METHODS: The CLIMEX model was developed to evaluate climatic suitability, while the soil suitability was scored based on five soil characteristics. The final areal suitability for potato cultivation was classified into 4 levels: very suitable, suitable, marginal, and unsuitable. RESULTS: Overall, 36.5% of South Korea had very suitable climate, but areas with the best values for soil conditions were approximately 10% of the climatically suitable areas. When considering the climate and soil conditions simultaneously, climatic suitability and soil condition were inversely related, resulting in only 1.2% of optimal areas with Jeju Island as the most suitable area. CONCLUSIONS: Because both climate and soil conditions need to be suitable for growing crops, this study can provide potential paddy-cultivation areas for potato cultivation and a method for evaluating suitable areas for crop cultivation.

Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques.

The demand for rapid and nondestructive methods to determine chemical components in food and agricultural products is proliferating due to being beneficial for screening food quality. This research investigates the feasibility of Fourier transform near-infrared (FT-NIR) and Fourier transform infrared spectroscopy (FT-IR) to predict total as well as an individual type of isoflavones and oligosaccharides using intact soybean samples. A partial least square regression method was performed to develop models based on the spectral data of 310 soybean samples, which were synchronized to the reference values evaluated using a conventional assay. Furthermore, the obtained models were tested using soybean varieties not initially involved in the model construction. As a result, the best prediction models of FT-NIR were allowed to predict total isoflavones and oligosaccharides using intact seeds with acceptable performance (R2p: 0.80 and 0.72), which were slightly better than the model obtained based on FT-IR data (R2p: 0.73 and 0.70). The results also demonstrate the possibility of using FT-NIR to predict individual types of evaluated components, denoted by acceptable performance values of prediction model (R2p) of over 0.70. In addition, the result of the testing model proved the model's performance by obtaining a similar R2 and error to the calibration model.

Classification of geographical origin of kimchi by volatile compounds analysis using an electronic nose.

Food authenticity is one of the largest concerns in recent days. As kimchi has been a global food, its production origin has been important issue, particularly due to the large import from China. Among the potential methods, electronic nose which can measure volatile compounds in foods is considered to be a powerful device for identifying country of production. This study is to classify 69 kinds of kimchi produced in South Korea (39) and China (30) by analyzing volatile compounds in kimchi using electronic nose-mass spectrometry. Two widely used multivariate analyses, discriminant function analysis and principal component analysis, were used. Results showed that both multivariate analyses can completely separate Korean and Chinese kimchi using 10 kinds of molecular weights among 10-160 amu. The results indicate that the volatile compounds in kimchi are a suitable target to determine the geographical origin of kimchi.

Ensemble evaluation of the potential risk areas of yellow-legged hornet distribution.

Invasion of alien species facilitated by climate change and human assistant is one of global threats that cause irreversible damages on the local flora and fauna. One of these issued species, Vespa velutina nigrithorax du Buysson, 1905 (Hymenoptera:Vespidae), is a significant threat to entomofauna, including honeybees, in the introduced regions. This wasp is still expanding its habitats, prioritizing the development of a reliable species distribution model based on recently updated occurrence data. Therefore, the aim of this study was to evaluate the potential areas that are climatically exposed to V. v. nigrithorax invasion globally and in South Korea, where the wasp has caused severe damage to local ecosystems and apiculture after its recent introduction. We developed a new global scale ensemble model based on CLIMEX and Maxent models and applied it to South Korea using field survey data. As a result, risky areas were predicted to be temperate and subtropical climate regions, including the eastern USA, western Europe, Far East Asia, and small areas in South America and Australia. In particular, South Korea has a high potential risk throughout the country. We expect that this study would provide fundamental data for monitoring the environmental risks caused by V. v. nigrithorax using advanced species distribution modeling.

Effects of Temperature, Relative Humidity, and Carbon Dioxide Concentration on Growth and Glucosinolate Content of Kale Grown in a Plant Factory.

The growth of plants and their glucosinolate content largely depend on the cultivation environment; however, there are limited reports on the optimization of ambient environmental factors for kale grown in plant factories. This study was conducted to investigate the effects of temperature, relative humidity, and the carbon dioxide (CO2) concentration on kale growth and glucosinolate content in different growth stages of cultivation in a plant factory. Kale was grown under different temperatures (14, 17, 20, 23, and 26 °C), relative humidities (45, 55, 65, 75, and 85%), and CO2 concentrations (400, 700, 1000, 1300, and 1600 ppm) in a plant factory. Two and four weeks after transplantation, leaf samples were collected to evaluate the physical growth and glucosinolate contents. The statistical significance of the treatment effects was determined by two-way analysis of variance, and Duncan's multiple range test was used to compare the means. A correlation matrix was constructed to show possible linear trends among the dependent variables. The observed optimal temperature, relative humidity, and CO2 range for growth (20-23 °C, 85%, and 700-1000 ppm) and total glucosinolate content (14-17 °C, 55-75%, and 1300-1600 ppm) were different. Furthermore, the glucosinolate content in kale decreased with the increase of temperature and relative humidity levels, and increased with the increase of CO2 concentration. Most of the physical growth variables showed strong positive correlations with each other but negative correlations with glucosinolate components. The findings of this study could be used by growers to maintain optimum environmental conditions for the better growth and production of glucosinolate-rich kale leaves in protected cultivation facilities.

Localized Delivery of Theranostic Nanoparticles and High-Energy Photons using Microneedles-on-Bioelectronics.

The low delivery efficiency of light-responsive theranostic nanoparticles (NPs) to target tumor sites, particularly to brain tumors due to the blood-brain barrier, has been a critical issue in NP-based cancer treatments. Furthermore, high-energy photons that can effectively activate theranostic NPs are hardly delivered to the target region due to the strong scattering of such photons while penetrating surrounding tissues. Here, a localized delivery method of theranostic NPs and high-energy photons to the target tumor using microneedles-on-bioelectronics is presented. Two types of microneedles and flexible bioelectronics are integrated and mounted on the edge of surgical forceps. Bioresorbable microneedles containing theranostic NPs deliver the NPs into target tumors (e.g., glioblastoma, pituitary adenoma). Magnetic resonance imaging can locate the NPs. Then, light-guiding/spreading microneedles deliver high-energy photons from bioelectronics to the NPs. The high-energy photons activate the NPs to treat tumor tissues by photodynamic therapy and chemotherapy. The controlled thermal actuation by the bioelectronics accelerates the diffusion of chemo-drugs. The proposed method is demonstrated with mouse tumor models in vivo.

Application of Ohmic-Vacuum Combination Heating for the Processing of Senior-Friendly Food (Multiphase Food): Experimental Studies and Numerical Simulation.

The popularity of senior-friendly food has been increasing as the world enters the age of an aging society. It is required that senior-friendly food products are processed with the new concept of processing techniques that do not destroy the nutritional and sensory values. Ohmic heating can be an alternative to conventional heating methods for processing senior-friendly food with retaining excellent taste and quality because of less destruction of nutrients in the food. In this study, the ohmic-vacuum combination heating system was developed to process a multiphase type of senior-friendly food. Changes in physical and electrical properties of senior-friendly model foods were investigated depending on the experimental conditions such as vacuum pressure intensity and vacuum pretreatment time. Numerical simulations based on the experimental conditions were performed using COMSOL multiphysics. The ohmic-vacuum combination heating method with agitation reduced the heating time of the model food, and non-uniform temperature distribution in model food was successfully resolved due to the effect of vacuum and agitation. Furthermore, the difference was found in the hardness of solid particles depending on the vacuum treatment time and intensity after the heating treatment. The ohmic-vacuum combination heating system appeared effective when applying for the senior-friendly foods in multiphase form. The simulation results matched reasonably well with the experimental data, and the data predicted through simulation could save the cost and time of experimentation.

Estimation of carcass weight of Hanwoo (Korean native cattle) as a function of body measurements using statistical models and a neural network.

OBJECTIVE: The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. METHODS: Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. RESULTS: The R2 values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R2 values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. CONCLUSION: The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.

Discrimination study between carcass yield and meat quality by gender in Korean native cattle (Hanwoo).

OBJECTIVE: The aim of this study was to identify a distribution pattern of meat quality grade (MQG) as a function of carcass yield index (CYI) and the gender of Hanwoo (bull, cow, and steer) to determine the optimum point between both yield and quality. We also attempted to identify how pre- and post-deboning variables affect the gender-specific beef quality of Hanwoo. METHODS: A total of 31 deboning variables, consisting of 7 pre-deboning and 24 post-deboning variables from bulls (n = 139), cows (n = 69), and steers (n = 153), were obtained from the National Institute of Animal Science (NIAS) in South Korea. The database was reconstructed to be suitable for a statistical significance test between the CYI and the MQG as well as classification of meat quality. Discriminant function analysis was used for classifying MQG using the deboning parameters of Hanwoo by gender. RESULTS: The means of CYI according to 1+, 1, 2, and 3 of MQG were 68.64±2.02, 68.85±1.94, 68.62±5.88, and 70.99±3.32, respectively. High carcass yield correlated with low-quality grade, while high-quality meat most frequently was obtained from steers. The classification ability of pre-deboning parameters was higher than that of post-deboning parameters. Moisture and the shear force were the common significant parameters in all discriminant functions having a classification accuracy of 80.6%, 71%, and 56.9% for the bull, cow, and steer, respectively. CONCLUSION: This study provides basic information for predicting the meat quality by gender using pre-deboning variables consistent with the actual grading index.

Statistical modeling for estimating glucosinolate content in Chinese cabbage by growth conditions.

BACKGROUND: Glucosinolate in Chinese cabbage (Brassica campestris L. ssp. pekinensis (Lour.) Rupr) has potential benefits for human health, and its content is affected by growth conditions. In this study, we used a statistical model to identify the relationship between glucosinolate content and growth conditions, and to predict glucosinolate content in Chinese cabbage. RESULT: Multiple regression analysis was employed to develop the model's growth condition parameters of growing period, temperature, humidity and glucosinolate content measured in Chinese cabbage grown in a plant factory. The developed model was represented by a second-order multi-polynomial equation with two independent parameters: growth duration and temperature (adjusted R2 = 0.81), and accurately predicted glucosinolate content after 14 days of seeding. CONCLUSION: To our knowledge, this study presents the first statistical model for evaluating glucosinolate content, suggesting a useful methodology for designing glucosinolate-related experiments, and optimizing glucosinolate content in Chinese cabbage cultivation. © 2018 Society of Chemical Industry.

Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging.

BACKGROUND: There is a need to minimize economic damage by sorting infected seeds from healthy seeds before seeding. However, current methods of detecting infected seeds, such as seedling grow-out, enzyme-linked immunosorbent assays, the polymerase chain reaction (PCR) and the real-time PCR have a critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to evaluate the potential of visible/near-infrared (Vis/NIR) hyperspectral imaging system for detecting bacteria-infected watermelon seeds. RESULTS: A hyperspectral Vis/NIR reflectance imaging system (spectral region of 400-1000 nm) was constructed to obtain hyperspectral reflectance images for 336 bacteria-infected watermelon seeds, which were then subjected to partial least square discriminant analysis (PLS-DA) and a least-squares support vector machine (LS-SVM) to classify bacteria-infected watermelon seeds from healthy watermelon seeds. The developed system detected bacteria-infected watermelon seeds with an accuracy > 90% (PLS-DA: 91.7%, LS-SVM: 90.5%), suggesting that the Vis/NIR hyperspectral imaging system is effective for quarantining bacteria-infected watermelon seeds. CONCLUSION: The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds. © 2016 Society of Chemical Industry.

Multivariate classification of the geographic origin of Chinese cabbage using an electronic nose-mass spectrometry.

An electronic nose-mass spectrometry (EN-MS) that profiles volatile compounds is a candidate device for identifying the geographic origin of cultivation of agricultural products when an adequate algorithm is derived. The objectives of this study were to apply two types of multivariate analysis, discriminant function analysis (DFA) and principal component analysis (PCA), to the volatile compounds detected by an EN-MS for the geographic classification of Chinese cabbage cultivated in Korea (42 samples) or in China (29 samples). DFA showed that Chinese cabbage from Korea were completely separable from those originating in China with 12 volatile compounds among the 151 detected. PCA revealed that Chinese cabbage data fell into two completely separable origins of Korea and China. This is the first study involving EN-MS data of volatile compounds with multivariate statistics to discriminate the geographical origin of Chinese cabbage, with further applications for other agricultural products.

Optimal fluorescence waveband determination for detecting defective cherry tomatoes using a fluorescence excitation-emission matrix.

A multi-spectral fluorescence imaging technique was used to detect defective cherry tomatoes. The fluorescence excitation and emission matrix was used to measure for defects, sound surface and stem areas to determine the optimal fluorescence excitation and emission wavelengths for discrimination. Two-way ANOVA revealed the optimal excitation wavelength for detecting defect areas was 410 nm. Principal component analysis (PCA) was applied to the fluorescence emission spectra of all regions at 410 nm excitation to determine the emission wavelengths for defect detection. The major emission wavelengths were 688 nm and 506 nm for the detection. Fluorescence images combined with the determined emission wavebands demonstrated the feasibility of detecting defective cherry tomatoes with >98% accuracy. Multi-spectral fluorescence imaging has potential utility in non-destructive quality sorting of cherry tomatoes.

Detection of starch adulteration in onion powder by FT-NIR and FT-IR spectroscopy.

Adulteration of onion powder with cornstarch was identified by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra of 180 pure and adulterated samples (1-35 wt % starch) were collected and preprocessed to generate calibration and prediction sets. A multivariate calibration model of partial least-squares regression (PLSR) was executed on the pretreated spectra to predict the presence of starch. The PLSR model predicted adulteration with an R(p)2 of 0.98 and a standard error of prediction (SEP) of 1.18% for the FT-NIR data and an R(p)2 of 0.90 and SEP of 3.12% for the FT-IR data. Thus, the FT-NIR data were of greater predictive value than the FT-IR data. Principal component analysis on the preprocessed data identified the onion powder in terms of added starch. The first three principal component loadings and ß coefficients of the PLSR model revealed starch-related absorption. These methods can be applied to rapidly detect adulteration in other spices.